Method.

The sample includes 12,247 noninstitutionalized men more than 50 years in 11 European countries. Multivariate logistic regression models estimated the impact of physical health, health behaviors, availability of social support, social participation, citizenship, time since immigration, socioeconomic status (SES), and employment on the mental health of immigrants.

Results.

Immigrants face 1.60 increased odds of depression despite a physical health advantage, evidenced by 0.74 lower odds of chronic illness. SES and availability of social support were predictive, though acculturation measures were not. Decomposition analysis revealed that only approximately 20% of the variation in depression rates between immigrants and native-born peers were explained by commonly cited risk factors.

FROM 1975 to 2005, the migrant population worldwide doubled, with 56 million living in Europe and 41 million in North America (Carta, Bernal, Hardoy, & Haro-Abad, 2005). By 2010, immigration rates increased even further, with immigrants comprising nearly 10% of the population across the European Union (EU27), and well above 20% in some countries (Vasileva, 2011). Older immigrants comprise a rapidly growing fraction of older adults in Europe and in the United States. In Germany, the migrant population aged 60 and older has doubled nearly every decade (White, 2006). In the Netherlands, immigrants more than 60 years in the two largest migrant groups, Turks and Moroccans, have experienced a growth of approximately 112% between 1996 and 2003 (White, 2006). Thus far, much of the literature examining immigration and health has focused on working-age immigrants, documenting consistently that, despite higher risk, immigrants exhibit better physical health than their native-born counterparts during their working years (Cunningham, Ruben, & Narayan, 2008). However, findings pertaining to the mental health implications of immigration have been equivocal (Acevedo-Garcia, Bates, Osypuk, & McArdle, 2010; Choi, 2012; Gee, Kobayashi, & Prus, 2004). In particular, findings documenting the impact of immigration on the mental health of older immigrants have been largely neglected.

Depression has been linked to discrimination, and social disadvantage, suggesting that immigrants may be at uniquely high risk (Breslau et al., 2011). Older immigrants may be at disproportionately high risk because depressive symptoms are more prevalent in older persons and in those of low socioeconomic status (SES; Blazer, 2003). Depression has significant social and financial costs. The annual economic cost of depression has been estimated at €118 billion in 2004 for 28 European countries and at $83 billion annually in the United States (Greenberg et al., 2003; Sobocki, Jonsson, Angst, & Rehnberg, 2006). Thus far, few studies have examined depression in older immigrants, and those that have focused primarily on single countries, younger immigrants and those from a single country of origin (Black, Markides, & Miller, 1998; Fossion et al., 2002; Gonzalez, Haan, & Hinton, 2001). In this study, we examine whether immigrants aged 50 and older living in 11 European countries exhibit higher risk for depression relative to native-born Europeans.

Although working-age immigrants are typically physically healthier than the domestic-born population, it is unclear whether it extends to mental health or whether this advantage is sustained in later life. Findings estimating the impact of immigration on depression have been inconclusive. For example, some studies examining the risk of depression among Hispanic immigrants generally support the notion of an immigrant advantage (Alegria, Canino et al., 2008; Cook, Alegria, Lin, & Guo, 2009; Grant et al., 2004; Moscicki, Locke, Rae, & Boyd, 1989). Others have shown the opposite, finding that Hispanic immigrants have higher rates of depression (Gonzalez et al., 2001). Compared with U.S.-born Mexican Americans, Black et al. (1998) found that immigrant women in H-EPESE were at significantly greater risk for depression, whereas male immigrants were at less risk. Of the few studies specifically examining older immigrants, Gerst, Al-Ghatrif, Beard, Samper-Ternent, and Markides (2010) found that older Mexican American immigrants were at higher risk for depressive symptoms compared with U.S.-born counterparts.

In the European context, the findings are equally mixed, with many countries reporting that immigrants experience higher rates of depression and anxiety (Carta et al., 2005). In some countries, like Sweden, virtually all immigrant groups report higher risk of depression, whereas in others the risk seems to affect only certain subgroups (e.g., Irish immigrants living in the U.K.) (Ryan, Leavey, Golden, Blizard, & King, 2006; Tinghog, Hemmingsson, & Lundberg, 2007). Although several studies suggest that immigration is predictive of depression, recent data from the European Social Survey suggest that low SES, not immigration, explains the higher risk among immigrants (Missinne & Bracke, 2012). In fact, in some countries, migration has been shown to improve mental health. Using a natural experiment, Stillman, McKenzie, and Gibson (2009) demonstrated that randomly selected Tongans who emigrated to New Zealand experienced improvements in mental health postmigration, suggesting that increased agency and immigration itself may be protective. Given their physical health advantage and the strong association between physical and mental health in later life, it is possible that immigration may have protective benefits for mental health (Beekman et al., 1997; Lenze et al., 2001).

Differences in the age and selection of the samples, inclusion of various immigrant groups, and variation in measures used to estimate depression make it difficult to reconcile these conflicting findings. Furthermore, few studies have been able to compare depression rates among immigrants cross-nationally and by country of origin due to data limitations. This has resulted in a somewhat fragmented understanding of the burden of depression among immigrants worldwide.

Conceptual Models and Hypothesis

In this article, we examine two key questions. First, are older European immigrants at higher risk for depression compared with their native-born counterparts? Second, do risk factors commonly believed to underlie the vulnerability of immigrants explain potential health disparities between immigrants and the native-born population? Because immigrants disproportionately face hardships, including loss of social status, limited social and emotional support, lower income, and higher job insecurity, a social stress model has been used to predict poorer mental health among immigrants (Berry, Kim, Mindle, & Mok, 1987; Gerst et al., 2010; Kuo, 1976; Pumariega, Rothe, & Pumariega, 2005). This model predicts that immigrants are at higher risk for depressive symptoms due to migration stressors; however, the effect of migration may be mitigated somewhat by acculturation, often measured by time since immigration (Alegria, Canino et al., 2008; Burnam, Hough, Karno, Escobar, & Telles, 1987). Some recent findings emphasize the impact of agency over structure, suggesting that immigrants may be more resilient, have better mental health than the native-born population, and may even gain from being uprooted (Burnam et al., 1987; Gong, Xu, Fujishiro, & Takeuchi, 2011; Kuo & Tsai, 1986). Although seemingly divergent, taken together these frameworks suggest that were it not for their positively selected physical health (and possibly mental health), immigrants might experience much worse mental health outcomes following their move. Given their superior physical health and the robust connection between physical and mental health, one might assume lower rates in immigrants relative to their native-born counterparts. Immigrants’ superior physical health advantage lessens after exposure to stressors, despite acculturation and resilience, and mental health likely suffers from similar exposures. We hypothesize that older immigrants living in Europe are likely to exhibit robust physical health advantages due to positive selection, although they may not experience similarly exceptional mental health. This is one of the first studies to examine both the mental health of older immigrants across Europe, framing a more comprehensive picture of immigrant health in later life.

Method

Sample Population

The sample is taken from The Survey of Health, Ageing, and Retirement in Europe (SHARE, Wave 1 Release 2), a prospective observational study comprising a randomly selected sample of 31,115 noninstitutionalized men and women aged 50 and older living in Austria, Germany, France, Switzerland, Belgium, Sweden, Denmark, the Netherlands, Spain, Italy, Greece, and Israel in 2004. Data from Israel were excluded as Israel was founded in 1948. Individual response rates varied from only 33% in Switzerland to 69% in France, with an average response rate of 48% (De Luca & Peracchi, 2004). Surveys were administered by professional survey agencies in an attempt to reduce sampling error, interpretation, and recall biases.

Measures

Dependent variables.—Mental Health: Depressive symptomatology was assessed using the EURO-D scale, a well-established 12-item scale validated in several cross-European studies of depression and against the Centers for Epidemiologic Studies Depression (CES-D) scale (Prince, Beekman et al., 1999; Prince, Reischies et al., 1999). The EURO-D scale asks respondents to rate the levels at which they had experienced feelings of depression, pessimism, wishing death, guilt, irritability, tearfulness, fatigue, sleeping troubles, loss of interest, loss of appetite, reduction in concentration, and loss of enjoyment during the preceding month. We used a dichotomized EURO-D measure, defined as a EURO-D score greater than 3, which has been validated against clinically relevant indicators as the level corresponding to a clinical diagnosis of depression (Prince, Harwood, Thomas, & Mann, 1998; Prince, Reischies et al., 1999). A dichotomized measure was used as it best aligns with a clinical outcome, yielding results more comparable with previous studies using a similar analytical approach. The estimate of Cronbach’s α of the EURO-D scale in this study is 0.72. In the sample of native born, Cronbach’s alpha was slightly higher (0.76), but was lower among the immigrants (0.66). To confirm that the EURO-D results correspond to a clinical diagnosis of depression in both groups, results were compared with respondents’ self-reported psychiatric history, including episodes of major depression, and CES-D responses.

Independent variables.—Immigration: Post-WWII migration in Europe can be characterized by three main phases: labor migration (1950–1973 with the onset of the oil crisis), restrained migration (1974–1988), and East-West migration and asylum seekers/refugees (1980s to 1992) (Zimmermann, 1995). Labor migration was spurred by strong economic growth in Western European countries, including Germany, Austria, Belgium, the Netherlands, Switzerland, Denmark, and Sweden. These countries primarily recruited manual laborers from Southern Europe, often implementing temporary guest worker (Gastarbeiter) programs. Concurrently, former colonial powers experienced substantial migrant flows from their respective former colonies: migrants from Pakistan or India came to Great Britain, whereas France received migration from North Africa. Although the guest worker schemes aimed to encourage temporary residence, many migrants stayed permanently and are now comprising an aging population of immigrants in Europe. As a result, many older immigrants in Europe, and in our sample, arrived as labor migrants from 1950s to 1970s.

In our analyses, immigration status is the primary independent variable. Immigrants were identified by reporting that they were born outside their country of residence. They also provided the year in which they arrived and their country of origin. The sample was restricted to immigrants who arrived in the host country post-1949 to avoid war-related displacement which was common immediately following WWII. The sample consists of 12,182 men 50 years and older residing in 11 European countries, of which 657 are immigrants (5.4%). Table 1 presents summary statistics. Table 2 presents the distribution of immigrants by host country. Nearly 60% of the immigrants surveyed had acquired the citizenship in the host country. Time since immigration was calculated as the difference between survey year (2004) and year of immigration reported by participants (Table 1). Given the age of immigrants (mean = 60.9 [SD = 8.5]) and the time since immigration (mean = 32.4 years [SD = 13.8]), the age at migration is estimated to be 28 years (SD = 14.7), indicating that immigrants overwhelmingly arrived after finishing school, and only few arrived as children. The countries of origin that were most represented in the sample include Germany (9.4%), Italy (9.3%), Morocco (5.8%), Turkey (5.8%), and Algeria (5.5%). This is consistent with the migration from Northern Africa and Southern Europe to Western Europe, largely due to the end of colonization and guest worker programs popular during that period. Due to the age and timing of immigrants in our sample, it is likely that many immigrants were labor migrants who participated in “guest-worker” programs. The sample was restricted to men because many share a common experience of labor migration. Women moving to and within Europe during this time period emigrated for more diverse reasons, such as family reunification, labor, education, or refugee status. As a result, women in this sample had a more heterogeneous migration experience and were thus excluded from this study.

Additional covariates.—Physical health was defined by two measures: experiencing more than two chronic diseases and having more than one activity of daily living (ADL) limitation. The presence of chronic disease (e.g., cardiovascular disease, hypertension, high cholesterol, diabetes, lung disease, asthma, arthritis, osteoporosis, cancer, ulcers, Parkinson’s Disease, cataracts, hip or femoral fractures, or other unmentioned conditions) was ascertained by responses to a battery of questions in the following form: “Has a doctor ever told you that you have… ?” ADL limitations were self-reported.

Age (in years), age squared, employment status, and SES were included in all models. SES was measured using household income and education. Income was measured using equivalized-household income (calculated by adjusting the income by the square root of the number of persons living in a household) adjusted for purchasing power parities. This measure of income better adjusts for cross-national differences in purchasing power. Educational attainment was classified using the 1997 International Standard Classification of Education (ISCED-97) created by the United Nations Educational, Scientific and Cultural Organization (UNESCO, 2006). Given cross-national variation in educational systems, years of education must be adjusted to reflect high school equivalency. As such, the ISCED-97 transforms data from different systems into a comparable international framework. It has been validated and used extensively in cross-national European studies (Börsch-Supan & Jürges, 2005). Employment status was measured using dummy variables for currently working, being retired. The omitted categories comprise unemployed and individuals out of the labor force for other reasons than retirement.

Health behaviors were estimated using current smoking (measured as smoking vs. not smoking) and drinking (consuming more than two drinks daily or drinking five to six times a week vs. drinking less than five times a week and less than two drinks daily). Availability of family support was defined by three measures: marital status (married vs. unmarried), number of children, and having children living nearby (at least one child within a 5-km radius vs. no children or only children living farther away than 5 km). Social participation was coded as positive if respondents reported participating in one or more of the following during the past month: care for a sick or disabled adult or provision of help for a family member, friend, or neighbor; voluntary or charity work; participation in education or training course; participation in sport or social club; participation in religious organization; or participation in a political or community organization.

Acculturation was measured using time since immigration and citizenship status. These are both strongly correlated with language use, social interaction, and an increased ability to successfully pursue life plans in the host country (Dawson, Crano, & Burgdoon, 1996; Salant & Lauderdale, 2003). Country of origin has also proven important in predicting health outcomes and acculturation and was also included in the models (available from the authors upon request). Summary statistics for these variables are also presented in Table 1.

Analysis

Multivariate logistic regression models estimated the relationship between immigration and mental health (depressive symptomatology), controlling for age, age squared, physical health, employment status, health behaviors, household income, education, family structure, social integration, citizenship status, and country fixed effects. Country fixed effects are an effective way to control for cross-national differences in factors such as public sentiment toward immigration, immigration policies, health care systems, and general macroeconomic indicators such as income and inequality, without having to determine whether differences stem from a particular unobserved variable. Modeling these unobserved factors as fixed effects allows for correlation between them and included covariates. Despite variation in social welfare and immigration policies and public sentiment in host countries during the 1950s and 1960s, most European countries during that period experienced an influx of labor migrants. Although migration experiences vary, adjusting for individual risk factors and country fixed effects illuminates risks common to aging immigrants throughout Europe.

In a second step, we examine change in the immigration coefficient of the logistic regressions after including (a) health behaviors and physical health status, (b) family and social support and social participation, (c) acculturation measures (citizenship status and time since immigration), and (d) employment status and SES. Changes in the immigration coefficient indicate that the given independent variables explain some variation in the effect of immigration. For instance, a decrease in the immigration coefficient after including SES variables would indicate that part of the immigrant effect is due to the lower SES of migrants. In a third step, we investigate this possibility further by running separate logistic regression models with all the explanatory variables separately for immigrants and nonimmigrants, and we decompose the immigration effect into the fraction explained by observable characteristics compared with the fraction unexplained by the variables. This decomposition is a more formal test of the hypothesis that other variables associated with immigration, not immigration, per se, explain differences in health outcomes. The unexplained part reflects factors associated with the experience of immigration. These could include (but are not limited to) discrimination in the host country, loss of social support networks in the origin country, and limited social mobility, among other factors. This analysis also highlights whether some factors, such as education, have differential impact on health outcomes for native-born versus immigrants.

Results

Mental Health

Across all countries, older immigrants face significantly higher risk of depression compared with nonmigrants, exhibiting 1.71 [1.39, 2.11] higher odds of depression (Table 3). Younger age, working or retirement (vs. unemployment or homemaking), higher educational attainment, and being married are associated with lower rates of depression. Underscoring the relationship between physical and mental health, depression is strongly associated with chronic illness and ADL limitations. Rates of depression are significantly higher in Italy, Spain, and France illustrating the north–south gradient. Immigrants also display a significant physical health advantage compared with nonmigrants, experiencing 0.71 [0.57, 0.89] lower odds of having two or more chronic diseases and no difference in ADL limitations. These results highlight a stark contrast between physical and mental health of immigrants in later life, whereby immigrants are at significantly higher risk of depression despite lower risk of chronic illness. Citizenship status does not seem to confer any independent advantage, nor, if taken as a measure of acculturation, does it indicate convergence in physical health to levels exhibited by nonmigrants in the host country. Given that citizenship is obtained after several years of residence, this finding is somewhat unexpected. Conversely, time since immigration is associated with increased risks of chronic disease for immigrants with 1.02 [1.00, 1.03] increased odds of chronic illness for each year the migrant stays in the host country.

Health behaviors, family support, and social participation.—Table 3 first presents a parsimonious model in which immigrants face 1.88 [1.54, 2.29] increased odds of depression when controlling only for country fixed effects and a quadratic function of age. Controlling for health behaviors, chronic illness, and functional limitations, the immigration coefficient increases due to the better physical health of immigrants. Conversely, the immigration coefficient is reduced after controlling for family and social support, social participation, and SES, revealing that the association between poor mental health and immigration is partly due to less social support and social participation and lower SES among immigrants. Importantly, citizenship and time since immigration, do not mediate the relationship between immigration and depression.

Table 4 presents separate logistic regressions for immigrants and nonimmigrants. In addition, we estimated a pooled model for immigrants and nonimmigrants and included an interaction between migration status and all explanatory variables. The t-statistic for this interaction indicates whether the coefficient is different for immigrants compared with nonimmigrants. Because of the relatively small sample size for immigrants, those differences are often not statistically significant. There are, however, some notable differences in the size of coefficients on some explanatory variables between immigrants and nonimmigrants. Education is more strongly associated with depression among immigrants than among nonimmigrants, although this difference is not statistically significant on the p < .05 level. Furthermore, retirement is not associated with depression among immigrants, whereas among nonimmigrants retired people are less likely to have depressive symptoms. It is also instructive to examine the differences in the country fixed effects for immigrants and nonimmigrants. Interestingly, immigrants are worse off in the Nordic countries and the Netherlands where rates of depression at the population level are relatively low, especially compared with the rates in Southern Europe. Overall, observable differences between immigrants and nonimmigrants are only able to explain around 20% of the raw difference in prevalence of depression between those groups, whereas around 80% remain unexplained and are reflected in different coefficient estimates for immigrants. (We use the Stata command nldecompose for this decomposition.) Only a small fraction of the observed differences in mental health problems between immigrants and native born can be explained through observable differences between those groups. This indicates that immigration itself has an effect on mental health.

Odds Ratios Depicting Relationship Between Depression and Explanatory Pathways for Immigrants and Nonimmigrants and t-Test for Equality of Coefficients

Discussion

This study examined whether older immigrants in 11 European countries experience higher likelihood of depression compared with their native-born counterparts. Few studies have focused on the mental health of immigrants in later life (Sole-Auro & Crimmins, 2008). Those that have examined depression in older immigrants present conflicting findings that are irreconcilable due to differences in the samples, methodology, and definitions of depression (Stillman et al., 2009; Syed et al., 2006; Van Der Wurff et al., 2004). Although immigrant groups are heterogeneous both within and across countries, immigrants share important commonalities that may influence their health later in life. We found that immigration was strongly predictive of depressive symptoms among male immigrants aged 50 and older, even after controlling for sociodemographic characteristics, physical health, employment, acculturation, and the availability of family and social support. Decomposing the gap in depression rates illustrates that only one fifth of the gap in depression rates between immigrants and nonimmigrants is explained by these factors. This is surprising given that much of the literature has focused on these factors to explain immigrant vulnerability (Takeuchi, Zane et al., 2007; Tinghog et al., 2007; Van Der Wurff et al., 2004). Second, given the strong correlation between physical and mental health, it is surprising that the superior physical health of immigrants relative to native born was not protective for their mental health. These findings suggest that the immigration experience is associated with an increased risk of depression even years after emigrating, and that acculturation may not be as protective as previously thought. Physical health may still have a protective effect, suggesting that immigrants’ mental health could have been even worse were they not to experience a physical health advantage.

Our results reinforce findings that immigrants often endure hardship, especially psychosocial stress, for years following migration (Berry et al., 1987; Gerst et al., 2010; Kuo, 1976; Pumariega et al., 2005). These findings are somewhat consistent with the social stress model, in that the model predicts that immigrants experience higher levels of social stress and as a result are more likely to experience depressive symptoms. However, our results do not fully support the notion that acculturation alleviates the stress associated with immigration. The effect of acculturation factors (time since immigration and citizenship) is not significant. Whereas obtaining citizenship might suggest that immigrants are committed to staying and perhaps less likely to be adversely influenced by the immigration experience, we do not find this to be the case. Immigrants in this study are largely acculturated given that respondents have resided in their host country for a long time and were proficient in the language of the host country (since all surveys were administered in the official language). As a result, depression rates may be even higher for other immigrant groups, especially those less acculturated and undocumented persons. Our results are more consistent with the agency-based model that suggests that acculturation may be negatively associated with mental health (Takeuchi, Alegria, Jackson, & Williams, 2007). However, this model suggests that immigrant health converges to the population average over the course of acculturation. Our finding that immigrants are worse-off relative to their native-born counterparts for all durations of stay suggests that immigrants may be worse off for reasons related to immigration and not because they are converging to the population health.

With respect to physical health, our results are consistent with the “healthy migrant effect,” as immigrants in our sample experience lower risk of chronic disease and ADL limitations despite higher rates of occupational stress and lower income. Much of this advantage may be explained by initial selection and lower postmigration susceptibility to chronic diseases in the host country. Time since immigration, a measure indicating duration of stay, suggests that immigrants who have been in the host country for a longer period of time are at worse health relative to immigrants who have been in the country for a shorter duration. Immigrants whose duration of stay is longer exhibit physical health that is close to the population average of the host country. Consistent with prior studies, we also find a gradient effect since the time since immigration seems to attenuate initial health advantages, suggesting that acculturation does not improve health (Angel, Buckley, & Sakamoto, 2001). This association holds even controlling for age and age squared. However, given the cross-sectional nature of our data, these results should be interpreted with caution.

Limitations

Although this article presents strong evidence bearing upon the late-life physical and mental health of immigrants to European countries, it has three important limitations. First, data are cross-sectional limiting causal inference. It is possible that country-level shocks would contribute to cross-national differences in immigrant health, however country fixed-effects were employed to control for this. A second limitation is not accounting for endogeneity in the immigration decision and possibly to remigration in old age. However, given that sicker immigrants are most likely to return home, our findings may actually underestimate the implications of migration for late-life mental and physical health.

Although the relative small number of immigrants did not allow a detailed estimation of interaction effects between migration status and characteristics of host and origin countries, but the sample size is sufficiently large to estimate an average effect with precision. Studies using representative samples of the population face the problem of having relatively small numbers of immigrants given that their share in the population is small. Specialized studies of the immigrant population, on the other hand, will typically lack the required detailed measures of health status. Though not underrepresented, immigrants were not specially targeted in SHARE, and interviews were conducted in the official country language. This may have resulted in a smaller number of immigrants and selection of immigrants who have acclimated and are more conversant and perhaps more acculturated. Assuming this to be true, our results seem even more striking, as they represent the best off immigrants. Differences in answering styles across countries could pose a limitation. While all cross-national studies face this limitation, we attempt to minimize this bias using measures that have been validated and employed frequently in comparative international studies.

Conclusions

Reflecting on post-war migration polices toward Italian guest workers, Swiss author Max Frisch, remarked, “We called for workers, and people came (Wir riefen Arbeitskräfte, und es kamen Menschen).” This observation underscores the potential long-term consequences of immigration, namely, that there are significant health, financial, and social strains associated with a growing population of aging immigrants. Increasing immigration across the European Union and United States has sparked much debate regarding the role and future of immigrants in modern society, in particular whether immigrants are an asset or a drain on the economy. Poor health in later life could decrease productivity and result in early retirement, whereas morbidity postretirement could also result in large health care costs and costs associated with caregiving (Mutchler, Burr, Massagli, & Pienta, 1999; Mutchler, Prakash, & Burr, 2007).

Given the superior physical health of immigrants compared with nonimmigrants in our study, claims that immigrants are sicker and are likely to overutilize health services may be overstated, if not unfounded. However, high rates of depression among immigrants are concerning. Future studies should examine health care utilization among immigrants and the role of barriers to access, particularly for mental health services. Although acculturation is not significant in our study, we do find that immigrant vulnerability is lower for those who experience high levels of social support and social engagement. It seems that the ability to engage in social activities, appeal to social supports when needed, and participate in the labor force that are most important in maintaining mental health (Carta et al., 2005; Mulvaney-Day, Alegria, & Sribney, 2007). Cultural differences, lack of language proficiency, and lower levels of health literacy may also pose significant barriers to quality care, particularly for depression. Better understanding the labor and social conditions of immigrants, the transition from the labor force into retirement is critical to designing interventions aimed at alleviating the disproportionate mental health burden (LaMontagne, Keegel, Vallance, Ostry, & Wolfe, 2008).

Funding

This research was supported by the National Institute on Aging, Grant T32 AG000186-22 (K.L.), and the NSF-IGERT program, “Multidisciplinary Program in Inequality & Social Policy” at Harvard University (Grant 0333403) (K.L.). The SHARE data collection has been primarily funded by the European Commission through the 5th framework program (project QLK6-CT-2001-00360 in the thematic programme Quality of Life). Additional funding came from the U.S. National Institute on Aging (U01 AG09740-13S2, P01 AG005842, P01 AG08291, P30 AG12815, Y1-AG-4553-01, and OGHA 04-064). Data collection for wave 1 was nationally funded in Austria (through the Austrian Science Foundation, FWF), Belgium (through the Belgian Science Policy Office), France (through CNAM, CNAV, COR, Drees, Dares, Caisse des Dépôts et Consignations et le Commissariat Général du Plan), and Switzerland (through BBW/OFES/UFES). The SHARE data collection in Israel was funded by the U.S. National Institute on Aging (R21 AG025169), the German-Israeli Foundation for Scientific Research and Development (G.I.F.), by the National Insurance Institute of Israel.

Acknowledgments

We would like to thank Stephanie Stuck for help in providing us with the country of origin data. We would like to acknowledge insightful and instructive comments from Christopher Jencks and from members of the MEA Seminar. K. Ladin and S. Reinhold planned the study. K. Ladin wrote the paper. K. Ladin and S. Reinhold oversaw data analysis. S. Reinhold performed all statistical analyses. European Commission through the 6th framework program (projects SHARE-I3, RII-CT-2006-062193, and COMPARE, CIT5-CT-2005-028857) is gratefully acknowledged.

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